It appears that both full heterogeneity model as well as the qualitative differences model have the same -2LL value, which should not be the case since we are dropping a parameter in the letter (I am told).
What is it that I'm doing wrong? Are my starting value set incorrectly? I tried various values and the same output is repeated.

Hello Tim,
Thanks for your reply.
It has been pointed out to me that the -2LL value for the main model one (I compare the submodels to it) is exactly the same for the sub model in which I test for qualitative sex differences in my sample. Both lines - as in your table - lines 1 and 2 show value of 22697.06.
I've been advised to change the starting values to obtain differential -2LL values, despite I tried that I see no change in them.
It is very difficult for me to interpret this output. And it is very possible, due to being so new to twin modelling, that I simply am lacking the experience in seeing the right differences between models.

You've found a bug in mxModel(), where the 'name' argument is being processed after all the other arguments, and it should be processed before the other arguments. Are you certain that you want to create a new submodel within unSexADEFit? It appears that you want to modify the contents of the unSexADEFit, instead of creating a new submodel. But if it is your intent to create a new submodel, then use the following as a workaround:

Thanks for your speedy response. I am still having trouble with the script. I am trying to test a univariate ADE model where I a) set limitations for quantitative and qualitative sex differences and b) run a sub model by dropping D.

I think the first step is to address the sex limitations. I am running into errors when I get to the sex limitation submodels, including:

+ unSexADESub1Fit <- mxRun(unSexADESub1Model)
Error: unexpected symbol in:
"
unSexADESub1Fit"
> unSexADESub1Fit <- mxRun(unSexADESub1Model, intervals=T)
Running unSexADESub1
Warning message:
In model 'unSexADESub1' NPSOL returned a non-zero status code 1. The final iterate satisfies the optimality conditions to the accuracy requested, but the sequence of iterates has not yet converged. NPSOL was terminated because no further improvement could be made in the merit function (Mx status GREEN).
> univADESumm <- summary(unSexADESub1Model)
> summary(unSexADESub1Model)

Here is my script thus far. Thank you in advance for any suggestions of help you have to offer!

unSexADEModel <- mxModel("unSexADE",
mxModel("ADE",

# ADE Model
# Matrices declared to store a, d, and e Path Coefficients
## TRANSLATING THE CODE ## Three matrices are set up to hold the
# path coefficients for each of the sources of variance considered
# in the model. They are 1x1 matrices with one element to be
# estimated, which is given a .6 starting value. As the matrix
# contains only one element, we assigned one label ("a11").
# Its name is different from the name of the matrix ("a") which
# in turn is different from the name for the R object (pathA) that
# will store the matrix with all its arguments.

# Combine Groups
## TRANSLATING THE CODE ## All the objects used in the algebra
# for the expected covariance matrices now have to be included
# into both the MZ and DZ models, so they are combined in a list
# named 'pars', which is then included in the 'modelMZ', 'modelDZ'
# and 'AdeModel' objects.
parsM <- list( pathA, pathD, pathE, covA, covD, covE )
parsF <- list( pathK, pathL, pathM, covK, covL, covM )